SSES is an R package that contains code for specifying and running a landscape scale social ecosystems model (Carruthers et al. 2018). The package contains in-line help for specifying landscape models and running analyses.
The default landscape object is for the BC Trout fishery that includes 584 stocked lakes and 9 population centres each with four angler classes.
The model is also represented in an SSES Shiny App that is available both locally (is in the R package) and online.
The SSES App will function on low resolution monitors but, due to interacting with a high resolution map, works best on 1080p monitors or preferably higher. As with all html webpages, if you run into issues with the layout, try zooming in/out using ctrl-mouse wheel or ctrl +/-.
This document:
SSES is freely available online.
You can also run the App locally on your computer. To do so install the R package and use the SLICK() function:
library(devtools)
install_github("blue-matter/SSES")
library(SSES)
Shiny("SSES")
The process for using the App follows the steps:
Step 1. Select lakes (Ext. Selection tab)
Step 2. Change management (Regulations and/or Stocking tabs)
Step 3. Recalculate landscape effort (Recalculation button)
Step 4. Compare outcomes (Outcomes)
Step 5. Create a new management scenario (Options),
Repeat steps 1-5 for a new management scenario and so on.
Selection occurs on the left-hand side and is facilitated by a navigable map. Specification of alternative management scenarios, graphing of outputs etc is carried out using the tabs on the right-hand side of the App:
Six stocking types are modelled in the B.C. trout lakes landscape:
In many decision makings context there is a state variable of interest (e.g. population numbers) that like performance metrics has a projected future. Unlike performance metrics, state variables also have a historical reconstruction that provides important context for projected outcomes.
Blue Matter
Butterworth, D.S., Punt, A.E. 1999 Experiences in the evaluation and implementation of management procedures. ICES Journal of Marine Science, 5: 985-998, http://dx.doi.org/10.1006/jmsc.1999.0532.
Cochrane, K L., Butterworth, D.S., De Oliveira, J.A.A., Roel, B.A., 1998. Management procedures in a fishery based on highly variable stocks and with conflicting objectives: experiences in the South African pelagic fishery. Rev. Fish. Biol. Fisher. 8, 177-214.
Punt, A.E., Butterworth, D.S., de Moor, C.L., De Oliveira, J.A.A., Haddon, M. 2014. Management strategy evaluation: best practices. Fish and Fisheries. 17(2): 303:334.
4.1 Social Ecological Systems Models